Fractional-Order PID Controllers for Temperature Control: A Review

Jamil, Adeel Ahmad; Tu, Wen Fu; Ali, Syed Wajhat; Terriche, Yacine; Guerrero, Josep M.

doi:10.3390/en15103800

Cited by 46 publications

(25 citation statements)

References 94 publications

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“…4b. 21 The PID controller has proportional (P), integral (I), and differential (D) parts. The proportional (P) control can respond quickly to errors, thereby reducing them within a short time.…”

Section: Temperature Control Systemmentioning

confidence: 99%

Portable dual-channel blood enzyme analyzer for point-of-care liver function detection

Sang,

Cheng,

et al. 2023

Analyst

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Section: Temperature Control Systemmentioning

confidence: 99%

Portable dual-channel blood enzyme analyzer for point-of-care liver function detection

Sang,

Cheng,

et al. 2023

Analyst

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“…PID Based PSS PID-PSS ensures a robust control performance. It operates a function that provides an appropriate torque on the generator rotor by compensating the phase lag between the machine's electrical torque and the exciter input [7][8][9][10][11][12][13][14][15][16][17][18][19][20]. The transfer function of the PID_PSS is given by Equation (3):…”

Section: Power System Stabilizer (Pss)mentioning

confidence: 99%

Power System Stability Enhancement Using a Novel Hybrid Algorithm Based on the Water Cycle Moth-Flame Optimization

et al. 2022

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Poor control of the power grid can lead to a total system collapse, causing significant economic losses and possible damage to security and social peace. Therefore, improving power system stability, particularly transient stability, has become one of the major research topics. This paper proposes a developed modeling approach that provides the optimal stabilizer parameters of the control devices, aiming at improving the electrical network stability by minimizing the angular speed deviation in the presence of a severe disturbance event using a novel hybrid algorithm called Water Cycle-Moth Flame Optimization (WCMFO). The main advantages of the proposed method are the speed of response and its efficient exploration and exploitation ability to attain the best solution quality. This is achieved by imposing a thermodynamic incident (an abrupt change in mechanical torque) on the well-known test model (SMIB), Single Machine Infinite Bus. To test the effectiveness of the proposed method, Power System Stabilizer (PSS), Proportional-Integral-Derivative (PID-based PSS), and Fractional Order-PID (FOPID-based PSS) are implemented to control and ensure the system’s ability to return to a stable state in the presence of this fault. The achieved experimental outcomes have proven the superiority, and efficiency of the developed approach (WCMFO) in terms of damping the oscillations and reducing the overshot, with an improvement of 44% over the Water Cycle Algorithm (WCA), Moth-Flame Optimization (MFO), and Artificial Ecosystem Optimization (AEO). It is envisaged that the proposed method could be very useful in the design of a practical high-performance power system stabilizer.

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“…T D represents the differential time constant. d stands for the calculated bias, and t signifies the time [23].…”

Section: D(s) � U(s) E(s)mentioning

confidence: 99%

Application of PID Control and Improved Ant Colony Algorithm in Path Planning of Substation Inspection Robot

Kang

Wang

2022

Mathematical Problems in Engineering

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The purpose is to improve the effect of substation inspection and ensure the safety of power consumption in human society. First, this work discusses the current substation inspection-oriented robot path planning situation. Then, the proportional integration differentiation (PID) control algorithm is introduced and optimized. Ant colony algorithm (ACA) is improved. The substation inspection-oriented RPP model is designed based on the PID algorithm and optimized ACA (the proposed model is denoted as the Ant-PID algorithm). Afterward, the Ant-PID algorithm is compared with the PID control algorithm and ACA. The results show that the longest robot path of the proposed Ant-PID algorithm in different data sets is about 28 m. The shortest is about 26 m, and the number of optimal solutions is maintained at about 45–49. By comparison, the average response time of the PID algorithm is about 25 s to 28 s. The shortest response time of ACA is about 24 s, the shortest average response time is about 27 s, and the longest is about 30 s. The average response time of the proposed ant PID model is about 17 s to 20 s. Therefore, the Ant-PID algorithm can improve the substation inspection robots’ path planning effect. The research results provide technical support for improving the effect of substation inspection and contribute to social power transmission.

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Fractional-Order PID Controllers for Temperature Control: A Review

Cited by 46 publications

References 94 publications

Portable dual-channel blood enzyme analyzer for point-of-care liver function detection

Portable dual-channel blood enzyme analyzer for point-of-care liver function detection

Power System Stability Enhancement Using a Novel Hybrid Algorithm Based on the Water Cycle Moth-Flame Optimization

Application of PID Control and Improved Ant Colony Algorithm in Path Planning of Substation Inspection Robot

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